We investigate the empirical performance of the long-standing state-of-the-art exact TSP solver Concorde on various classes of Euclidean TSP instances and show that, surprisingly, the time spent until the first optimal solution is found accounts for a large fraction of Concorde’s overall running time. This finding holds for the widely studied random uniform Euclidean (RUE) instances as well as for several other widely studied sets of Euclidean TSP instances. On RUE instances, the median fraction of Concorde’s total running time spent until an optimal solution is found ranges from 0.77 for $$n=500$$n=500 to 0.97 for $$n=3{,}500$$n=3,500; on TSPLIB, National and VLSI instances, we pegged it at 0.86, 0.74 and 0.61, respectively, with a tendenc...
We present an “adaptive multi-start ” genetic algorithm for the Euclidean traveling salesman problem...
Humans need to solve computationally intractable problems such as visual search, categorization, and...
This paper is an example of the growing interface between statistics and mathematical optimization. ...
We study the empirical scaling of the running time required by state-of-the-art exact and inexact TS...
We study the empirical scaling of the running time required by state-of-the-art exact and inexact TS...
The travelling salesman problem (TSP) is one of the most prominent NP-hard combinatorial optimisatio...
The time complexity of problems and algorithms, i.e., the scaling of the time required for solving a...
We study exact algorithms for {\sc Euclidean TSP} in Rd. In the early 1990s algorithms with nO(n√) r...
We study exact algorithms for Euclidean TSP in $\mathbb{R}^d$. In the early 1990s algorithms with $n...
AbstractAn algorithm for empirically calculating the expected number of optimal and near-optimal sol...
We revisit the classic task of finding the shortest tour of $n$ points in $d$-dimensional Euclidean ...
We consider the metric Traveling Salesman Problem (Δ-TSP for short) and study how stability (as defi...
The Euclidean algorithm on the natural numbers N = f0, 1,... g can be specified succinctly by the re...
We revisit the classic task of finding the shortest tour of $n$ points in $d$-dimensional Euclidean ...
Automated algorithm configuration is a powerful and increasingly widely used approach for improving ...
We present an “adaptive multi-start ” genetic algorithm for the Euclidean traveling salesman problem...
Humans need to solve computationally intractable problems such as visual search, categorization, and...
This paper is an example of the growing interface between statistics and mathematical optimization. ...
We study the empirical scaling of the running time required by state-of-the-art exact and inexact TS...
We study the empirical scaling of the running time required by state-of-the-art exact and inexact TS...
The travelling salesman problem (TSP) is one of the most prominent NP-hard combinatorial optimisatio...
The time complexity of problems and algorithms, i.e., the scaling of the time required for solving a...
We study exact algorithms for {\sc Euclidean TSP} in Rd. In the early 1990s algorithms with nO(n√) r...
We study exact algorithms for Euclidean TSP in $\mathbb{R}^d$. In the early 1990s algorithms with $n...
AbstractAn algorithm for empirically calculating the expected number of optimal and near-optimal sol...
We revisit the classic task of finding the shortest tour of $n$ points in $d$-dimensional Euclidean ...
We consider the metric Traveling Salesman Problem (Δ-TSP for short) and study how stability (as defi...
The Euclidean algorithm on the natural numbers N = f0, 1,... g can be specified succinctly by the re...
We revisit the classic task of finding the shortest tour of $n$ points in $d$-dimensional Euclidean ...
Automated algorithm configuration is a powerful and increasingly widely used approach for improving ...
We present an “adaptive multi-start ” genetic algorithm for the Euclidean traveling salesman problem...
Humans need to solve computationally intractable problems such as visual search, categorization, and...
This paper is an example of the growing interface between statistics and mathematical optimization. ...